Submitted
Abstract Submission
HOMOCYSTEINE – A STRONG BIOMARKER FOR PREDICTING CHRONIC KIDNEY DISEASE IN PATIENTS WITH TYPE 2 DIABETES
Oral Presentation
Scientific Research Abstract
Diabetes
Author's Information
4
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Loi Ho Ngoc hongocloi@ump.edu.vn University of Medicine and Pharmacy at Ho Chi Minh City School of medicine Ho Chi Minh Vietnam *
Tuan Le Quoc dr.lequoctuan@ump.edu.vn University of Medicine and Pharmacy at Ho Chi Minh City School of medicine Ho Chi Minh Vietnam -
Tien Tran Van vantien1307@yahoo.com University of Medicine and Pharmacy at Ho Chi Minh City School of medicine Ho Chi Minh Vietnam -
Tinh Tran Truong Trung trungtinhtran4321@gmail.com University of Medicine and Pharmacy at Ho Chi Minh City School of medicine Ho Chi Minh Vietnam -
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Abstract Content
Type 2 diabetes mellitus (T2DM) is highly prevalent worldwide, and diabetic kidney disease (DKD) is a major cause of end-stage renal disease, reduced quality of life, and increased healthcare costs. Although the albumin–creatinine ratio (ACR) and estimated glomerular filtration rate (eGFR) are standard markers of DKD, they are often insufficiently sensitive to detect early kidney involvement. Homocysteine (HCY), a sulfur-containing amino acid, is implicated in vascular and renal injury through endothelial dysfunction, oxidative stress, and inflammation; however, its usefulness as an early biomarker of DKD in T2DM remains uncertain. Therefore, this study aims to evaluate the role of HCY in the early detection of kidney damage in patients with T2DM.
This cross-sectional study included adults with T2DM attending the University Medical Center between January and June 2025. Patients using medications that could affect HCY levels or presenting with acute clinical conditions were excluded. Plasma HCY was measured by enzyme immunoassay, and eGFR was calculated using the CKD-EPI equation based on serum creatinine and cystatin C. CKD was defined as eGFR < 60 mL/min/1.73 m² and/or uACR ≥ 30 mg/g. Data were analyzed using STATA, and ROC curve analysis was performed to assess the predictive value of HCY for the development of CKD.
Among 210 patients (male:female ratio 1:1.5; mean age 64.85±10.38 years), mean HCY levels were significantly higher in those with DKD than in those without DKD (15.93±6.29 vs. 10.68±4.09 µmol/L). On univariable analysis, HCY showed good discriminative ability for DKD, with an AUC (0.79) and an optimal cutoff (11.37 µmol/L) by the Youden index, yielding sensitivity (76.2%) and specificity (78.4%). In a multivariable logistic regression model including clinical variables (age, sex, body mass index, systolic blood pressure) and laboratory parameters (HbA1c, fasting plasma glucose, HCY), HCY remained an independent predictor of DKD (OR 1.27; 95% CI 1.14–1.42; p < 0.05), and the model achieved a higher AUC of 0.8152, indicating improved predictive performance.
HCY levels were elevated in T2DM patients with CKD and independently associated with CKD risk, suggesting that in clinical practice HCY may be used both as an individual biomarker, with an optimal cutoff of approximately 11–12 µmol/L, and as a component of multivariable risk prediction models to stratify patients with diabetes according to their risk of CKD.
Type 2 diabetes mellitus; Chronic kidney disease; Homocysteine; Risk prediction model
https://storage.unitedwebnetwork.com/files/1305/8b40a81f83678ab94cdd9b2495ef8034.png
Clinical–laboratory model (age, sex, BMI, SBP, HbA1c, FPG, HCY) for predicting CKD in patients with T2DM
400
Loi
Ho Ngoc
hongocloi@ump.edu.vn
 
Presentation Details
Oral Presentation 2: Precision Diabetes: Management & Renal Protection
Mar. 20 (Fri.)
14:35 - 14:44
06